Astronomical Observatory: Cool Images

M20
Trifid Nebula, Elise Crull

The Science of M20
There’s a lot of science to be gleaned from this beautiful (if I may say so) image of M20. M20 is more commonly known as the Trifid Nebula, which is approximately 20 x 15 arcsecs in size and is found in the constellation Sagittarius. It is sometimes considered to be an extended part of the complex Lagoon Nebula.

The Trifid itself consists only of the reddish southern region; the blue region to the north is an unconnected reflection nebula. The Trifid is an emission nebula: it is mostly an HII region (which is why we see it as emitting in the red end of the optical spectrum) with some diffuse H-alpha regions along the edges. The three dark “stripes” in the HII region are absorption dust lanes- areas were the dust has a thickness such that the light of the stars behind it is extinguished. Other areas of extinction are visible in the image on either side of where the reflection and emission nebulae meet (the background is “blacker” there).

The stars behind the reflection nebula appear reddened due to the light scattering effects of the nebula (the nebula itself appears blue for this reason).

Data Received
from Rehoboth Observatory
Two fields: North and South
Three filters: Red, Visible, Blue
30 images of each field in Red and Visible
40 images of each field in Blue
All 60 sec. exposures
All 2x2 binning

Processing
Technique After
taking a detailed inventory of the data I’d gotten back from Rehoboth,
I calibrated the images according to standard procedure: I subtracted
the ghosts from all frames, subtracted a 60sec dark (from the same day
as the data to insure comparable camera temperatures), subtracted a bias
with 2x2 binning, and finally, grouped the images by filter and divided
them by the appropriate flat-field.
When all the images were calibrated, I aligned each color and field (a
total of 6 sets of aligned data), and then averaged each set (for a total
of 6 images). The alignment was done using the Manual-1 Star option in
MaxIm DL, and the averaging was done using Average (as opposed to Median).

After calibration,
alignment, and averaging, I created a mosaic of each filter individually.
This procedure took some playing: I began by cropping the images to get
rid of excess on the edges, and made sure both the north and south fields
were cropped to the same size. The remove bloom function was used on one
overexposed star in the northern field. Then I scaled the background of
each image using pixel math to comparable counts. I then played with the
histogram for both, setting them to be equal. After I was satisfied that
the histogram setting was displaying the data most adequately, I set the
backgrounds to be precisely the same in each field (using pixel math once
again). This is necessary for a good mosaic. After both fields were set,
I opened a new palette with the correct dimensions, and pasted in the
two images using a pixel blend width of 10 pixels, and disenabling the
“Background Equalization” option.

I now had three mosaics,
one in each filter. To bring out the unique “differentiation of
data” within each filter, I first made copies of the original mosaics,
lest anything go awry during my use of the Stretch function (which changes
the actual data). Utilizing the Gamma function in Stretch, I found optimal
pixel count ranges and gamma levels for each color, to bring up brightness
levels in more diffuse, faint regions of the image. The Stretch parameters
I used were as follows:
Red : gamma .25, min 1117, max 3000, 16-bit
Vis : gamma .15, min 1115, max 3000, 16-bit
Blue: gamma .15, min 1225, max 4000, 16-bit
After finding these parameters, I set the modified mosaics to these levels,
aligned all three images, and performed a color combine.

It turns out that
color combining the gamma-functioned images in Maxim does not succeed.
Therefore, these modified images were opened in CCDSoft5 and color combined
there. The final image (with red, visible and blue levels set equally)
was then saved as a JPEG file with 0% compression.

A few ghost-remnants
were visible in the final image. I opened up the JPEG in Paint, and using
the spray paint option, blended out the erroneously colored spots.